Degraded License Plate Recognition system for town buses on highway

Bing-Fei Wu, Hao Yu Huang, Yen Lin Chen, Hsin Yu Lin, Tsu Tian Lee, Chao Jung Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This study presented a Degraded License Plate Recognition (DLPR) to identify town buses on highway. Since the License Plates (LPs) of town buses are influenced by the external conditions and become hardly distinguished by the Optical Character Recognition (OCR) method. The proposed DLPR system adopts Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM)-for classification-based solution. The proposed system implements a two-level LPR, including LP localization and character recognition. For the recognition efficiency of the proposed system, two trained databases for LP localization and character recognition are reduced by the mathematical and feature-based approaches, respectively, and thus the searching time can be saved significantly. To certify the performance of recognizing the degraded LPs, the proposed system is demonstrated by physical degraded LP images, and thus the results reveal that the proposed system overcomes several degraded LP images with reasonable recognition accuracy.

Original languageEnglish
Title of host publication2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
Pages446-450
Number of pages5
DOIs
StatePublished - 14 Aug 2013
Event2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013 - Evry, France
Duration: 10 Apr 201312 Apr 2013

Publication series

Name2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013

Conference

Conference2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
CountryFrance
CityEvry
Period10/04/1312/04/13

Keywords

  • Histogram of Oriented Gradient (HOG)
  • License Plate Recognition
  • Pattern Recognition
  • Support Vector Machine (SVM)

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